{"paper_id":"dad4f292-20d7-43b3-876a-e33df753fc85","body_text":"Endometriosis (EMS) is a chronic gynecological disease characterized by pain and infertility. Long-term pain and infertility seriously affect patients’ physical and mental health and quality of life (QoL), and even lead to anxiety and depression. Hormonal and surgical treatments can temporarily relieve some of the symptoms, but the recurrence rate of endogynecology is high and the QoL of patients cannot be improved in the long term. [ 1 ]  Therefore, improving patients’ QoL is one of the main treatment goals of EMS.\nIn recent years, Health-Related Quality of Life (HRQoL) assessment has become an important endpoint in clinical research, especially for chronic diseases such as EMS. Patients’ perceptions of their well-being are a key component of disease impact. [ 2 ]  Previous studies have found that patients with EMS have lower HRQoL compared to normal subjects. Most of the existing tools for assessing QoL are universal scales, such as the MOS item short from health survey and the World Health Organization Quality of Life Scale, and it is still controversial whether such scales can truly, comprehensively, and validly evaluate the HRQoL of patients with EMS. [ 3 , 4 ]  On the one hand, the universal scale fails to include all the connotations of HRQoL in patients with EMS, such as infertility. [ 5 ]  On the other hand, the universal scale suffers from a lack of sensitivity in reflecting, for example, pain and its response to treatment. [ 6 , 7 ]\nCurrently, the most reliable EMS-specific QoL assessment tool is the Endometriosis Health Profile-30 (EHP-30) developed by Jones et al, recommended by the American Fertility Society and the European Society of Embryology and Reproduction for use in clinical studies of patients with EMS. [ 8 , 9 ]  The scale has been translated into French, German, Italian, Spanish, and Russian with good reliability and validity. [ 8 , 10 ]  However, due to the differences in values, systems, cultures, and families between China and Western countries, the Chinese version of the EHP-30 cannot fully reflect the characteristics of EMS patients in China. Furthermore, as healthcare shifts to the digital age, e-health literacy is becoming increasingly important in enabling patients to access information about their illness and make informed decisions about their treatment options. There is growing evidence that e-health literacy is associated with better disease understanding and self-management in patients with chronic diseases. [ 11 ]\nWe aimed to revise and evaluate the reliability and validity of the Chinese version of the EHP-30 and to construct a theoretical framework for e-health literacy in patients with EMS. Providing a reliable and efficient tool for assessing the QoL of patients with EMS paves the way for more personalized patient education and empowerment to manage this debilitating state.\n\nThis study was approved by the Ethics Committee of Wuxi Maternity and Child Health Care Hospital. The QoL assessment scale for EMS patients was finally formed through qualitative interviews and expert consultation with EMS patients, combined with literature analysis. The scale included 4 dimensions of physical function, mental and psychological function, social function, disease characteristics and treatment, and 38 items. According to the Likert 5-level scoring method, it is further divided into “very important, relatively important, generally important, relatively unimportant, and very unimportant,” corresponding to “5 points, 4 points, 3 points, 2 points, and 1 point.”\nA cross-sectional study was conducted on patients with pathological diagnosis of EMS in Wuxi Maternal and Child Health Hospital from January 1, 2023 to June 31, 2024. A total of 230 general information questionnaires and QoL assessment scales for EMS patients were distributed (228 were actually recovered). Two weeks after the end of the first survey, 30 patients were randomly selected and filled in the EMS patient QoL assessment form again to evaluate the test–retest reliability of the scale. At the same time, the criterion-related validity was evaluated by the EMS health scale EHP-30 (a total of 40 cases). (All patients signed written informed consent.)\nUsing discrete trend analysis, correlation coefficient method, factor analysis, and Cronbach coefficient method and other statistical methods to analyze the scale items and delete items that do not meet the statistical criteria.\nIt includes test–retest reliability analysis and internal consistency analysis, which are used to evaluate the consistency and stability of the scale. The test–retest reliability reflects the consistency of the scale across time. The test–retest reliability is generally considered to be ≥0.70 after 2 weeks of retest. Internal consistency reflects the internal consistency between different items, and Cronbach alpha (α) coefficient is used to evaluate the homogeneity of scale and dimension. The higher the Cronbach α coefficient, the more consistent the test content. In general, internal consistency should be ≥0.70.\nIt mainly includes structural validity and criterion-related validity to evaluate the accuracy, validity and correctness of the scale. Construct validity refers to the degree to which the structure and characteristics of the measured indicators can be measured. It is generally believed that this is the best validity evaluation index in the scale evaluation. The significance Sig value and Kaiser–Meyer–Olkin (KMO) values are used to determine whether the test item structure is reasonable. When the significance Sig < 0.05, it shows that the questionnaire has good structural validity. KMO test is used to compare the simple correlation coefficient and partial correlation coefficient between variables. When the KMO value < 0.6, sampling adequacy is poor; 0.6 ≤ KMO value < 0.8, sampling adequacy is average; 0.8 ≤ KMO value < 0.9, sampling adequacy is good; and 0.9 ≤ KMO value, sampling adequacy is very good. At the same time, the Chinese version of the EHP-30 scale was used as a tool to evaluate the criterion-related validity of the EMS QoL scale.\nIn this study, data analysis was conducted using statistical package for the social sciences 22.0 software. Missing data were appropriately handled in the 228 valid questionnaires. For missing data on key questions (such as those affecting QoL), listwise deletion was applied, while for noncritical missing data, mean imputation was used. These methods helped minimize the impact of missing data and ensured the representativeness of the sample. Extreme value detection was performed using box plots and  Z -scores, with any values >3 standard deviations from the mean considered outliers and excluded to prevent their influence on the analysis results. To ensure logical consistency, responses with contradictions (e.g., reporting severe pain but also indicating high QoL) were flagged and excluded from the analysis. Statistical analysis included descriptive statistics (mean, standard deviation, and frequency distributions), reliability testing using Cronbach α coefficient, and validity testing through exploratory factor analysis and correlation analysis. These analyses ensured the reliability and scientific validity of the study’s results.\n\nThe results of descriptive statistical analysis of the research data are as follows (Table  1 ).\nThe results of descriptive statistical analysis of the research data (n = 228).\nA total of 11 experts were invited for expert consultation, and all experts answered and scored the scale items. The experts are from Wuhan, Beijing, Shenzhen, Tangshan, Baotou, Amsterdam, and other places. The average working years of consultants were 22.77 years (SD = 8.97), with the longest working years of 38 years and the shortest of 6 years. Among the consultants, there are 5 PhDs and 5 Masters; 10 senior title personnel; 4 psychiatrists, 3 clinical nurses, 2 nursing specialists, 2 informatics specialists, and 2 artificial intelligence specialists, as detailed in Table  2 .\nBasic information of experts.\nThe scale items were adjusted through literature review and interviews, followed by expert consultation. Form a pre-survey version of the Chinese version of EHP-30, the following is the result of expert consultation (Table  3 ).\nChinese version of EHP-30 entry reservations.\nEHP-30 = endometriosis health profile-30, EMS = endometriosis.\nThe positive degree of experts: 11 copies of the first round of expert consultation form were issued and 11 copies were recovered. The recovery rate was 100%, reaching 70% of the standard requirements. Consulting experts gave strong support to this study.\nThe degree of authority of experts: data analysis shows that the expert authority coefficient is 0.914, indicating that the reliability of experts is high.\nConcentration of expert opinions: this study considers deleting items with mean < 4 or full score ratio < 0.5.\nThe results of the analysis of the discrete trend method are shown in Table  4 . The greater the coefficient of variation of the discrete trend method, the more obvious the discrete trend, and the better the ability to distinguish. The coefficient of variation of all items was >0.25. Therefore, all items are retained.\nDiscrete trend analysis.\nAccording to the correlation analysis results of each item and scale, the correlation coefficient between item 38 and scale is below 0.40, and the correlation coefficient is 0.398, which is close to 0.40. It is considered to be deleted, and the rest is retained. See Table  5  for details.\nResults of correlation coefficient analysis of various items.\nThe principal component factor analysis of the scale items is shown in Table  6 . After extracting the number of 4 factors, the 4 factors cumulatively explained 59.791% of the scale variables. The factor loads of all items are >0.50, and the load difference of the co-load items is >0.30, so all items are retained. In addition, we conducted factor analysis on a total of 38 questions. According to the 16 factors extracted from the scree plot (Fig.  1 ), the total variance interpretation is obtained. The 16 factors extracted can explain 62.289% of the total variance of 38 problems. That is to say, from a statistical point of view, the combination of different weight coefficients of these 16 factors can cover 38 problems. More than 60% of the information is actually to extract 16 main factors from 38 specific problems, which achieves a quantitative dimension reduction.\nPrincipal component factor analysis results.\nScree plot of Chinese version of quality-of-life assessment in EMS patients. EMS = endometriosis.\nCronbach α coefficient is a method to measure the reliability of the scale or test. It evaluates the degree of consistency between the items within the scale, that is, whether these items are measuring the same concept, attribute or skill. The Cronbach α coefficient was first proposed by American educator Lee Cronbach in 1951, and has become one of the most commonly used reliability analysis tools in social science research. The Cronbach α coefficient in this study scale is 0.780. After the item is deleted, the Cronbach α coefficient becomes smaller and all items are retained (Table  7 ).\nThe results of the Cronbach coefficient method analysis.\nThe α values of the 4 dimensions of this study are shown in Table  8 . The α coefficients of physical function, mental and psychological function, social function and disease characteristics, and treatment reliability coefficients are 0.728, 0.764, 0.783, and 0.7594, respectively. The α coefficients of the dimensions are between 0.7 and 0.9. The overall Cronbach α coefficient of the questionnaire data reaches 0.780, and the overall data reliability is relatively reliable.\nReliability analysis results.\nIt can be seen from Table  9  that the Sig value of the data is 0.000, and the KMO value is 0.773, indicating that the data of each dimension are independent of each other, which indicates that the validity of the questionnaire data is good.\nValidity analysis results.\nKMO = Kaiser–Meyer–Olkin.\nThe feasibility of the scale was evaluated by the acceptability of the scale and the time required to fill in the scale. A total of 230 scales were issued in the large sample survey, and 228 valid scales were received. The recovery rate was 99.13%, which was >85%, suggesting that the scale was highly accepted. The shortest completion time is about 3 minutes, the longest completion time is about 12 minutes, the average time is about 7 minutes, and the completion time is within a reasonable allowable range.\nIn summary, the final formal scale consists of 4 dimensions and 38 items. Among them, the physical function dimension includes 9 items, the mental and psychological function dimension includes 10 items, the social function includes 11 items, and the disease characteristics and treatment include 8 items. The reliability of the scale is high, and the higher the score in the scale item score, the higher the QoL of EMS patients.\n\nEMS is a chronic gynecological condition characterized by the presence of endometrial-like tissue outside the uterus, which can lead to severe pelvic pain, infertility, and substantial impairment in QoL. The prevalence of EMS among women of reproductive age underscores the urgency for improved diagnostic tools and management strategies that can alleviate the burden of this disease. The complexity of EMS symptoms and their impact on physical, mental, and social well-being necessitate comprehensive approaches to assess and enhance patient health outcomes.\nIn this study, we revised the Chinese version of the EHP-30 and evaluated its reliability and validity based on the phenotypic characteristics of EMS and the QoL level, based on an extensive literature review, qualitative interviews, and expert correspondence. Cronbach α coefficient ≥ 0.70, validity tests confirmed structural validity through exploratory factor analysis and correlation analysis, validity scale correlation validity used the Chinese version of the EHP-30 as a tool, and content validity achieved high-level endorsement through the method of expert judgment. Higher reliability and validity scores suggest that our scales are consistent and robust in capturing these subtle differences in QoL between individuals. [ 12 ] Our scale includes 4 dimensions: physical functioning, psychological functioning, social functioning, and disease characteristics and treatment options. It reflects the complex nature of EMS and its pervasive impact on patients’ lives. In addition to the revisions to the details of the 4 dimensions, we correlated higher scores on the scale with better QoL levels, not just for symptom management, but also emphasized the importance of holistic patient care, bridging interventions to improve physical symptoms with support for mental health and social functioning to improve overall QoL. [ 13 ]  In conclusion, our study provides valuable insights into assessing and improving the QoL of patients with EMS. It emphasizes the need for healthcare providers to adopt a multifaceted care strategy that addresses not only medical needs but also emotional and social needs.\nConsidering the multifaceted impact of the disease on physical, psychological, and social functioning, it is crucial to develop a theoretical framework for eHealth literacy among EMS patients. In addition, we constructed the first theoretical framework for eHealth literacy among EMS patients. The framework is expected to advance personalized care by more accurately assessing patient needs and facilitating targeted interventions, leading to significantly improved disease management outcomes. [ 14 , 15 ]  Incorporating psychosocial parameters into our theoretical framework for e-health literacy in patients with EMS provides a more comprehensive approach to patient education and self-management. By recognizing the importance of emotion management and self-perception in EMS, we can develop interventions that target symptom management and psychosocial support. This dual focus is critical to improving overall well-being and providing patients with knowledge about their condition. Our findings also emphasize the importance of eHealth literacy as a critical component of patient education and self-management. In an era of increasing access to digital health resources, equipping patients with the skills to effectively navigate these tools can lead to more informed decision-making and potentially better health outcomes. [ 16 ]  To sum up, our study emphasizes the need for a multidimensional assessment tool that encompasses not only the physical aspects but also the broader biopsychosocial aspects of EMS. Such a tool would be invaluable to clinicians seeking to provide holistic care that addresses all aspects that affect a patient’s QoL.\nCompared with foreign countries, the domestic research on the QoL of EMs patients started late, mainly based on the application of various scales. At present, the scales used to evaluate the QoL of EMs patients in China are all translated from foreign scales. Due to the differences in value, system, culture, family, and other aspects between China and Western countries, the Chinese scale does not fully fit China’s national conditions. Just as the scholar Jia Shuangzheng found in the process of sinicizing EHP-30: the Chinese version of EHP-30 has good reliability and validity in EMs patients. EMs patients have better acceptance, but the integrity of the sexual life dimension data is low. The researchers speculate that it is related to the influence of Chinese traditional culture on patients. The study also found that the 3 dimensions of patient–child relationship, medical professional feelings and self-image were different from the results of foreign surveys. It may be due to the fact that the EMs patients surveyed are mostly young and middle-aged, and have higher expectations for self-image, doctor’s requirements and mother–child relationship. The Chinese version of EHP-30 fails to reflect the above characteristics. Therefore, it is necessary to revise the Chinese version of EHP-30. This revision will include the above deficiencies, learn from each other, and build a new scale that is in line with national conditions and in line with Chinese expression habits.\nAlthough this study comprehensively assessed the reliability and validity of the QoL Scale for EMS patients and constructed a theoretical framework for e-health literacy, there are some limitations that should be explored. First, while the sample size was sufficient for preliminary analyses at our hospital, as a single-center pilot study, the sample size remains relatively small and may not fully represent the broader population of EMS patients in China. This limitation affects the generalizability of the results to a wider demographic. Future research should focus on multicenter validation to enhance the external validity of the findings and ensure they are applicable to diverse populations. Second, the current study did not account for potential inter-batch differences that may arise from using multiple datasets. Addressing these factors in future studies would help strengthen the robustness and generalizability of the results.\nThese results have important implications for enhancing patient care management strategies by providing healthcare professionals with a powerful tool to accurately assess the health-related QoL of patients with EMS. In addition, it paves the way for further research by including larger sample sizes, clinical validation, and multicenter studies to minimize batch effects. In the future, we will utilize the revised Chinese version of the EHP-30 to construct a management pathway for patients with EMS in the Chinese cultural context; establish a cohort, implement and evaluate the management pathway. In order to provide a reliable and efficient tool for healthcare professionals to assess the QoL of EMS patients in China, and to provide a basis for the implementation of active and effective therapeutic and nursing care measures to improve the QoL of EMS patients.\n\nConceptualization:  Hua Shi, Shangjin Li, Shaojie Zhao.\nData curation:  Hua Shi, Shangjin Li, Shaojie Zhao, Shasha Zhao.\nFormal analysis:  Hua Shi, Shangjin Li, Shasha Zhao.\nValidation:  Shasha Zhao.\nVisualization:  Rui Gu, Shasha Zhao.\nWriting – original draft:  Hua Shi, Shangjin Li, Shasha Zhao.\nWriting – review & editing:  Hua Shi, Shaojie Zhao, Rui Gu.","source_license":"CC0","license_restricted":false}